| Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi X Yue, Y Ni, K Zhang, T Zheng, R Liu, G Zhang, S Stevens, D Jiang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 534 | 2024 |
| Predicting drug-disease associations by using similarity constrained matrix factorization W Zhang, X Yue, W Lin, W Wu, R Liu, F Huang, F Liu BMC bioinformatics 19, 1-12, 2018 | 263 | 2018 |
| Predicting drug-disease associations and their therapeutic function based on the drug-disease association bipartite network W Zhang, X Yue, F Huang, R Liu, Y Chen, C Ruan Methods 145, 51-59, 2018 | 89 | 2018 |
| A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data R Liu, L Wei, P Zhang Nature machine intelligence 3 (1), 68-75, 2021 | 84 | 2021 |
| Identifying sepsis subphenotypes via time-aware multi-modal auto-encoder C Yin, R Liu, D Zhang, P Zhang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 48 | 2020 |
| Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports R Liu, P Zhang BMC medical informatics and decision making 19, 1-9, 2019 | 36 | 2019 |
| Estimating Individual Treatment Effects with Time-Varying Confounders R Liu, C Yin, P Zhang IEEE International Conference on Data Mining (ICDM), 2020 | 22 | 2020 |
| The application of artificial intelligence in the management of sepsis J Yang, S Hao, J Huang, T Chen, R Liu, P Zhang, M Feng, Y He, W Xiao, ... Medical Review 3 (5), 369-380, 2023 | 20 | 2023 |
| Estimating treatment effects for time-to-treatment antibiotic stewardship in sepsis R Liu, KM Hunold, JM Caterino, P Zhang Nature machine intelligence 5 (4), 421-431, 2023 | 14 | 2023 |
| CURE: A deep learning framework pre-trained on large-scale patient data for treatment effect estimation R Liu, PY Chen, P Zhang Patterns, 2024 | 8* | 2024 |
| Clinical connectivity map for drug repurposing: using laboratory results to bridge drugs and diseases Q Wen, R Liu, P Zhang BMC medical informatics and decision making 21, 1-11, 2021 | 7 | 2021 |
| Deconfounding actor-critic network with policy adaptation for dynamic treatment regimes C Yin, R Liu, J Caterino, P Zhang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 5 | 2022 |
| A computational framework for identifying age risks in drug-adverse event pairs Z Zhao, R Liu, L Wang, L Li, C Song, P Zhang AMIA Summits on Translational Science Proceedings 2022, 524, 2022 | 2 | 2022 |
| KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs R Liu, L Wu, P Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 8805-8814, 2024 | 1 | 2024 |
| Heterogeneous treatment effect estimation with subpopulation identification for personalized medicine in opioid use disorder S Lee, R Liu, W Song, P Zhang 2023 IEEE International Conference on Data Mining (ICDM), 1079-1084, 2023 | 1 | 2023 |
| A Deep Subgrouping Framework for Precision Drug Repurposing via Emulating Clinical Trials on Real-world Patient Data S Lee, R Liu, F Cheng, P Zhang arXiv preprint arXiv:2412.20373, 2024 | | 2024 |
| Using multiple drug similarity networks to promote adverse drug event detection B Padhi, R Liu, Y Yang, X Peng, L Li, P Zhang, P Zhang Heliyon 10 (22), 2024 | | 2024 |
| Teach Multimodal LLMs to Comprehend Electrocardiographic Images R Liu, Y Bai, X Yue, P Zhang arXiv preprint arXiv:2410.19008, 2024 | | 2024 |
| SubgroupTE: Advancing Treatment Effect Estimation with Subgroup Identification S Lee, R Liu, W Song, L Li, P Zhang arXiv preprint arXiv:2401.12369, 2024 | | 2024 |
| Estimating the Treatment Effects of Multiple Drug Combinations on Multiple Outcomes in Hypertension R Liu, L Li, P Zhang medRxiv, 2024.11. 10.24317054, 2024 | | 2024 |
Ping ZhangThe Ohio State UniversityVerified email at osu.edu